Online Self-Supervised Thermal Water Segmentation for Aerial Vehicles
We present a new method to adapt an RGB-trained water segmentation network to target-domain aerial thermal imagery using online self-supervision by leveraging texture and motion cues as supervisory signals. This new thermal capability enables current autonomous aerial robots operating in near-shore environments to perform tasks such as visual navigation, bathymetry, and flow tracking at night. Our method overcomes the problem of scarce and difficult-to-obtain near-shore thermal data that prevents the application of conventional supervised and unsupervised methods. In this work, we curate the first aerial thermal near-shore dataset, show that our approach outperforms fully-supervised segmentation models trained on limited target-domain thermal data, and demonstrate real-time capabilities onboard an Nvidia Jetson embedded computing platform. Code and datasets used in this work will be available at: https://github.com/connorlee77/uav-thermal-water-segmentation.
Code (1)
Tasks
SegmentationVisual NavigationSimilar Papers 제목 키워드 기반
Transformer-based Self-Supervised Fish Segmentation in Underwater Videos
Underwater fish segmentation to estimate fish body measurements is still largely unsolved due to the complex underwater environment. Relying on fully-supervised segmentation models requires collecting per-pixel labels, w…
Representation LearningSegmentationSelf-Supervised LearningBoosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation
In autonomous driving, thermal image semantic segmentation has emerged as a critical research area, owing to its ability to provide robust scene understanding under adverse visual conditions. In particular, unsupervised …
Autonomous DrivingDomain AdaptationImage SegmentationScene Understanding+4Self-supervised learning for hotspot detection and isolation from thermal images
Hotspot detection using thermal imaging has recently become essential in several industrial applications, such as security applications, health applications, and equipment monitoring applications. Hotspot detection is of…
Representation LearningSelf-Supervised LearningSparse Point-Guided Fusion of Supervised and Self-Supervised Learning Model for Seaweed Segmentation
The ocean plays a critical role in sustainable development, particularly in climate change mitigation. Among marine ecosystems, blue carbon ecosystems are recognized as important natural carbon sinks. In this context, th…
Self-Supervised LearningInstance SegmentationDeepAqua: Self-Supervised Semantic Segmentation of Wetland Surface Water Extent with SAR Images using Knowledge Distillation
Deep learning and remote sensing techniques have significantly advanced water monitoring abilities; however, the need for annotated data remains a challenge. This is particularly problematic in wetland detection, where w…
Knowledge DistillationSemantic Segmentation